Social networks are an important factor in the prevalence of obesity. Network-mediated interventions - interventions that intentionally leverage social networks to change behavior and improve health - have been successful at changing behaviors such as smoking, but have not yet been developed to address obesity. The translation of research on social networks and obesity into network-mediated interventions has been slow because the spread of relevant behaviors is poorly understood. Stochastic actor-based models now allow us to simultaneously control for numerous network effects and thus, disentangle and quantify how networks shape our behavior, and how our behavior shapes our networks. This represents great strides in methodological rigor. But the scientific community is limited in its ability to apply these methods to understanding behaviors related to adult obesity (e.g., physical activity) because adequate datasets do not exist. Therefore, we propose to leverage an ongoing family-based, community-based childhood obesity prevention intervention (U01HL103620, the GROW Study) with 460 Latino parents. By adding social network data collection to the GROW study's final data collection point (T6, 3 Years), the proposed study will create a dataset that is unique because it maps the social network of a well-characterized cohort over three years (Baseline, 1 Year, 3 Years). Very importantly, network measurements will be taken at the same time as objectively measured behaviors (e.g., physical activity, weight change), within a bounded network with minimal missing data. Our main research question is whether Latino parents can build new social ties to improve their physical activity and weight. Using the most advanced modelling techniques available, we will quantify social contagion of physical activity, examine the types of networks that spread (or constrain) physical activity and weight loss, as well as the positions in the social network that are able to start (or obstruct) th spread of physical activity and weight loss through the network. We propose to extend data collection beyond the plans of the GROW study, and to conduct an ambitious series of analyses that are distinct from the GROW study and not yet reported in the literature. Our long term goal is to advance the scientific community's understanding of how new social networks facilitate or constrain physical activity so that we can create more effective obesity prevention and treatment interventions. This proposal, a time-sensitive study, could result in significant gains in translational research on a serious - and intractable - public health problem for a relatively modest investment.